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arXiv · 2303.03128

Neural complexity -- Statistical-mechanical approach of human electroencephalograms

Dimitri Marques Abramov·Constantino Tsallis·Henrique Santos Lima
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Abstract

The brain is a complex system whose understanding enables potentially deeper approaches to mental phenomena. Dynamics of wide classes of complex systems have been satisfactorily described within $q$-statistics, a current generalization of Boltzmann-Gibbs (BG) statistics. Here, we study human electroencephalograms of typical human adults (EEG), very specifically their inter-occurrence times across an arbitrarily chosen threshold of the signal (observed, for instance, at the midparietal location in scalp). The distributions of these inter-occurrence times differ from those usually emerging within BG statistical mechanics. They are instead well approached within the $q$-statistical theory, based on non-additive entropies characterized by the index $q$. The present method points towards a suitable tool for quantitatively accessing brain complexity, thus potentially opening useful studies of the properties of both typical and altered brain physiology.

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Dimitri Marques Abramov, Constantino Tsallis, Henrique Santos Lima. 2023-03-06. Neural complexity -- Statistical-mechanical approach of human electroencephalograms. https://doi.org/10.1038/s41598-023-37219-5

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